Technologies That Foster Big Data Analytics

Technologies That Foster Big Data Analytics

When companies maximize the power of Big data, they gain a competitive advantage in the business world. This large volume of collected data not only helped businesses to unlock business growth opportunities, but it also enabled them to create well-informed decisions. For that reason, more and more businesses utilized Big data analytics to optimize their business operations. Moreover, the first step they did to reap its benefits is acquiring a business powered by fiber optics with the assistance of accredited fiber optic technicians.

It is as clear as day how Big data revolutionized the business world. And the best way to make the most out of it is by utilizing technologies that enabled Big data analytics.

Predictive Analytics

For a business to move forward, it is imperative for business owners to take well-calculated risks from time to time. And with the help of Predictive analytics solutions, business owners are able to identify the risks that are worth taking. The hardware and software used for Predictive analytics process Big data in order to discover, evaluate and deploy predictive scenarios. With this tool, business owners will be able to prepare for whatever that comes their way.

NoSQL Databases

Aside from Predictive analytics, another technology that helps in analyzing Big data is a NoSQL database. This database enabled companies to manage Big data efficiently across a scalable number of storage nodes. That said, NoSQL is better compared to other databases in terms of performance and scalability.

Knowledge Discovery Tools

At present, people all around the world create around 2.5 quintillion bytes of data every single day. And with the continuous development of the Internet of Things (IoT), that amount still has the potential to grow. For that reason, it became a necessity for businesses to update the data they use in their business operations. One way to do that is by mining structured and unstructured Big data from multiple sources with the help of Knowledge discovery tools.

Stream Analytics

It is common for businesses these days to process data in different formats that are stored in multiple platforms. Because of that, it became a challenge for companies to filter, aggregate and analyze this large volume of data. One solution that businesses used to address this is the utilization of the Stream analytics software. With this technology, they were able to manage data better and they were able to connect to external data sources easily.

In-memory Data Fabric

When it comes to dealing with Big data analytics, it is necessary to distribute these large volumes of data across system resources. And with an in-memory data fabric, this can be achieved with ease. Aside from the assistance that it provides in the distribution of Big data, it also enables low latency access and processing of the Big data on the attached nodes.

Distributed Storage

The corruption of Big data sources and independent node failures are bound to happen at some point when you’re handling Big data. But fear not, you can counter these mishaps by having a distributed file storage where businesses can place their replicated data.

Data Virtualization

One of the most utilized Big data technologies in distributed data stores nowadays is data virtualization. With this technology, applications are enabled to retrieve Big data without the need to implement technical restrictions.

Data Preprocessing

Other than the technologies mentioned above, data preprocessing software solutions are also prevalent among businesses that utilize big data analytics. This technology is widely used to manipulate data into a consistent format that can be used for further analysis. Although data preprocessing requires human oversight, its data preparation tools can help in accelerating the data sharing process.

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